Flourmills as elements in the economies and landscapes of towns and cities in NSW during the nineteenth century
Bibliographic record
Abstract
In every nineteenth century town in Europe, the USA, Canada and other European colonies of any size there would commonly be three significant buildings: at least one church, at least one pub and a flourmill, They supplied the needs of the populace for spiritual comfort, alcoholic release and what they perceived as essential food, The reason for a flourmill existing in so many places, whether they were close to or far from grain producing areas, was simple, Grain did not significantly deteriorate in being transported long distances, while stone-ground flour did, there was therefore a market for locally produced flour that contributed to the settlements' economy, Once they were built, how important they were for employment is hard to determine, The numbers employed to run a mill in NSW varied enormously from one mill type to another, from one place to another, from one period to another and even from one season to another, While most mills needed at least six men, some could require up to a hundred. What can be said is that most jobs around, a mill required skilled and often engineering know how, Grain came in various levels of softness or hardness and the machinery had to be adjusted to the different requirements of the grain types.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".